DataOps ETL Validator - Deeper Dive
July 21, 2022; 11:00 AM EST
A Deep Dive into DataOps ETL Validator.
Data enters your enterprise in a variety of means and varying quality. As it is moved and transformed to support the companies initiatives, there are many ways that the processes can introduce anomalies into the decision process. In this session, we will explore the application of ETL Validator to identify these issues so that they can be corrected early in the data cycle where the cost to repair these is minimized.
DataOps Data Quality Monitor - Deeper Dive
August 11, 2022; 11:00 AM EST
A Deep Dive into DataOps DQM- Data Quality Monitor.
Data that has entered your organization and comes to rest in your Data Warehouses or Data Lakes can still become corrupted for various reasons. This session will explore how this happens and show how Data Quality Monitoring can be your early warning signs to avoid costly mistakes down the road.
DataOps Test Data Manager - Deeper Dive
September 01, 2022; 11:00 AM EST
A Deep Dive into DataOps TDM- Test Data Manager.
Application testing has long been one of the primary ways to keep the integrity of your data assets in place. With the advent of a myriad of data privacy laws, it is no longer ok to take a copy of your production data for testing. This session will explore how you can create synthetic test data based on a sample of your production data and still comply with the data privacy laws.
BI Validator – How does it compliment DataOps Suite
September 22, 2022; 11:00 AM EST
A Deep Dive into BI Validator complimenting DataOps Suite.
In this webinar, we will explore the value that BI Validator brings to the overall DataOps approach as it is an integral part of the end-to-end overall solution.
Datagaps DataOps Suite - An Overview
A Power-Packed Webinar on Automating Testing for your data’s journey through the enterprise using DataOps Suite.
From the point of ingestion of data into your enterprise and as it moves through the organization, DataOps Suite provides the ability to validate the quality of the data, ensure anomalies have not been entered, and that your data transformations are working correctly.
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